I have read all of the comments on this thread and found a lot of them useful, so thanks.

I have an issue with the FM Model though. In the example files provided by the Add-In, the FMB regression is run using SMB, HML and Mkt_R as independent variables (IVs). Some other studies and examples in this thread also do the same. They therefore seek to explain how a portfolio is exposed to these various risk-factors (usually provided by K. French's website).

However, some other studies seek to assess the monotonic, or idiosyncratic, variation in stock returns. They tend to use market capitalisation (size), book-to-market ratio (value), momentum and market beta as the independent variables. The risk-factors (IVs) thus all include data for each firm. Earlier in this thread, it was mentioned that the risk-factors cannot currently take into account multiple series.

For some context, I am seeking see whether the variation in stock returns can be explained by the environmental performance of a firm - I understand that the Fama-French and Fama-Macbeth theories are the best ways to utilise control variables and make a robust analysis.

My questions are therefore the following:1. Is the Fama-Macbeth package on EViews solely for the use of K. French risk-factors? i.e. HMB, SML etc. 2. Am I overthinking everything...perhaps somebody knows an easy solution for my research question.3. The Fama-Macbeth method, as far as I am aware, is useful for assessing monotonic relationships. However, this relies on supplying independent variables that are firm specific (matrix-form). It seems to me that the Add-In performs the Fama-Macbeth procedure but does not allow for the analysis of individual stocks. Looking at others research, I am therefore not replicating their studies because my IVs are the general K. French factors and not the firm-specific factors..?

I have added my own stock returns into the fm_example workspace. My files are called er_01, er_02 etc. I can then perform the FMB regression: fmb er* hml smb mkt_rf. Because the risk factors (hml, smb, mkt_rf) are fixed for all dependent variables, er* is therefore regressed against fixed risk factors.

Is it possible to change the risk factors so that they are in matrix form? So that every er_# is regressed against its corresponding value, size and market beta?

I have attached the explanation in the academic paper that explains the use of firm-specific independent factors, and also proof of my FMB regression output with the K.French factors. This might help explain my confusion.

If you are asking whether you can force the addin to perform Fama-MacBeth on multiple sets of risk factors at the same time, the answer is no. Fama-MacBeth examines the risk premia from exposure to a common set of factors, not different factors for each return series. I suspect there is something you are not understanding about your problem.

i have to run several fama-macbeth regressions for my factors.I'm not that familiar with eviews but i think i understand how your code works.

i wanted to test if the hml factor yields the same risk premium and t-stat as it did in your example. I did it for a 30 industry and 49 industry portfolio and my results don't make any sense.... (slightly negative and insignificant, while hml in your example is positive and has a t-stat >2)

I think the issue is my portfolio... Did i write it in the right way? series* is my 49industry portfolio and pr* my 30 industry portfolio.

Okay, my question is not regarding the factors, but rather about the portfolio creation. In your file you name them 11 to 15 and than 21to 25, probably because it is a 5x5 portfolio. my question is if the way you name the portfolios has an impact on the fama macbeth regression.

It's not clear why you think the portfolio names would impact the regression. The portfolio names in the example are arbitrary (I downloaded the series from Ken French's data library and simply renamed them - the frenchdata add-in is an easy way to download). Furthermore the same set of factors is used for each regression in the initial Fama-Macbeth step, for example.

Hi everyoneI'm dealing with fama mcbeth regression but i cant realize the procedure.In fm regression i want to regress monthly returns on operating profitability. I have 100 stocks with monthly return data and annual operating profitability data for ten years. and i also have 3 control variables (b/m , r1,1 , r12,2). So please help me how to fit these data on fm regression because returns data are monthly but operating profitability data are annual. I dont know how can i relate monthly data with annual...having your assistance would be of great help. thanks.